The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Innovation resistance among mature consumers
Abstract
Purpose: The purpose of this paper is to investigate innovation resistance among mature consumers in the mobile banking context. The reasons inhibiting mature consumers' mobile banking adoption were compared to those of younger consumers. Design/methodology/approach: Following Ram and Sheth, resistance was measured with five barriers namely Usage, Value, Risk, Tradition and Image barriers. An extensive internet survey was implemented and 1,525 usable responses were collected, of which 370 respondents (24.3 percent) represented the mature consumer segment (age over 55) and 1,155 respondents (75.7 percent) represented the younger consumers. Findings: The empirical findings indicate that the value barrier is the most intense barrier to mobile banking adoption among both mature and younger consumers. However, aging appears to be related especially to the risk and image barriers; the most significant differences between mature and younger consumers' perceptions of mobile banking were related to input and output mechanisms of information, the battery life of a mobile phone, a fear that the list of PIN codes would be lost and end up in the wrong hands and the usefulness of new technology in general. Practical implications: The study has practical implications to marketers in different fields in that strategies to overcome resistance to innovations like mobile banking are discussed. Originality/value: Innovation resistance can be seen as a less developed concept in adoption research. While the majority of studies have focused on the success of innovations and reasons to adopt, this study empirically investigates the reasons preventing innovation adoption.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2003) · International Journal of Electronic Commerce · doi:10.1080/10864415.2003.11044275 · Cited by 5,715
Cited by
Online shopping drivers and barriers for older adults: Age and gender differences
Lian, J.-W., & Yen, D. C. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.04.028 · Cited by 660
Thakur, R., & Srivastava, M. (2014) · Internet Research · doi:10.1108/intr-12-2012-0244 · Cited by 606
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Algharabat, R. (2018) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2017.08.026 · Cited by 576
Leong, L.-Y., Hew, T.-S., Ooi, K.-B., & Wei, J. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.102047 · Cited by 528
Determinants of organic food consumption. A systematic literature review on motives and barriers
Kushwah, S., Dhir, A., Sagar, M., & Gupta, B. (2019) · Appetite · doi:10.1016/j.appet.2019.104402 · Cited by 443
Metadata
- Authors
- Laukkanen, T., Sinkkonen, S., Kivijärvi, M., & Laukkanen, P.
- Venue
- Journal of Consumer Marketing
- Publisher
- Emerald
- Published
- 2007-11-06
- Volume
- 24
- Issue
- 7
- Pages
- 419-427
- ISSN
- 0736-3761 (ISSN-L)
- OpenAlex
- W2023228027
- Cited by
- 423
- References
- 1
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Innovation resistance among mature consumers. https://app.cochat.ai/papers/10.1108/07363760710834834
- The paper
- Laukkanen, T., Sinkkonen, S., Kivijärvi, M., & Laukkanen, P. (2007). Innovation resistance among mature consumers. Journal of Consumer Marketing. https://doi.org/10.1108/07363760710834834
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.